The present invention relates to the field of image analysis.
Detection of salient image regions in natural images has been at the focal point in research in recent years. The most appealing property of saliency algorithms is that they capture the most informative image location without learning any information on a particular scene. This make these kind of algorithms highly versatile and beneficial for a wide range of applications ranging from object detection to image compression. Natural image saliency algorithms differ from one other by the type of distinctness they rely on. Theses types of distinctness may be divided into three major categories: patch distinctiveness, color distinctiveness and human priors.
Patch distinctiveness calculates some distance measure between all (or nearly all) image patches with the same size. A patch may be considered salient if it is different from nearly all other or most of the other image patches. Color distinctiveness identifies image areas which have unique color characteristics as compared to all other image areas. Human priors involves incorporating known priors on image organization and human gaze. The most prominent is the human tendency to place the photographed subject around the center of the image.
The foregoing examples of the related art and limitations related therewith are intended to be illustrative and not exclusive. Other limitations of the related art will become apparent to those of skill in the art upon a reading of the specification and a study of the figures.